Anti-scouring experimental device for road semi-rigid base material

Abstract

The invention discloses an anti-scouring experimental device for a road semi-rigid base material, which belongs to the technical field of detection and comprises a frame, a bearing cylinder, a scouring mechanism and an impeller off-bottom height adjusting system. Through the synergistic effect of an annular test piece state analysis module, a wear agent state analysis module, a scouring condition analysis module, a scouring state analysis module and an impeller height optimization module; a multi-stage state model is constructed based on geometric errors (inner ring flatness, wall thickness uniformity and roundness) of a test piece, wear agent characteristics (sand hardness, content and particle size grading) and scouring conditions (temperature, concentricity, flow velocity and rotating speed), and the height of the target impeller away from the bottom is dynamically output. The problem of experimental result deviation caused by fixed impeller height and static parameters of a traditional device is solved, and the precision and efficiency of anti-scouring testing are remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of testing technology, and in particular relates to a test device for the erosion resistance of semi-rigid road base materials. Background Technology

[0002] Semi-rigid road base courses are subjected to long-term water infiltration and vehicle erosion during service, making them prone to material loss and structural damage, directly affecting the service life of the road surface. Therefore, erosion resistance is one of the core indicators for evaluating the durability of base course materials, and precise experimental equipment is urgently needed for quantitative testing.

[0003] Traditional erosion resistance testing apparatuses often employ fixed impeller heights and static erosion conditions, failing to dynamically adjust the impeller height above the bottom to adapt to changes in specimen condition and abrasive properties. Furthermore, existing technologies neglect the synergistic effects of specimen geometric errors (such as roundness and wall thickness uniformity), abrasive conditions (sand particle size distribution, hardness, and temperature), and erosion conditions (flow velocity and concentricity), resulting in poor repeatability of experimental results and significant deviations from actual operating conditions. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an experimental device for testing the erosion resistance of semi-rigid road base materials, thus solving the aforementioned problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an experimental device for testing the erosion resistance of semi-rigid road base materials, comprising:

[0006] The impeller clearance height adjustment system is used to dynamically adjust the impeller clearance height, including:

[0007] The ring specimen state analysis module constructs a ring specimen state model based on the inner ring flatness error, wall thickness uniformity error, and roundness error, and outputs the ring specimen state coefficients.

[0008] The wear agent condition analysis module constructs an wear agent condition model based on sand hardness, sand content, and sand particle size distribution (0.5-1mm particle size percentage) and outputs wear agent condition coefficients.

[0009] The scouring condition analysis module constructs a scouring condition model based on the abrasive temperature under the abrasive state coefficient and the concentricity of the annular specimen and the impeller, and outputs the scouring condition coefficient.

[0010] The scouring state analysis module constructs a velocity-speed adaptation model based on the abrasive flow rate and impeller speed under the scouring condition coefficient and the state coefficient of the annular specimen, and outputs the velocity-speed adaptation degree.

[0011] The impeller clearance height optimization module constructs an impeller clearance height optimization model based on the baseline clearance height and the flow velocity-rotation speed adaptation, and outputs the target impeller clearance height.

[0012] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0013] Further technical solution: The highly optimized model is represented as follows:

[0014]

[0015] in, Indicates the height of the target impeller from the bottom. Indicates the height of the reference impeller from the bottom. This represents the fitness sensitivity coefficient. This indicates the flow rate-rotation speed fit threshold. This indicates the flow rate-rotation speed compatibility.

[0016] Further technical solution: The working principle of the scour status analysis module is as follows:

[0017] Import the abrasive flow rate into the formula The wear agent flow rate deviation index is obtained from the data. Indicates the abrasive flow rate. Indicates the optimal flow rate of the abrasive. Indicates the permissible deviation range of abrasive flow rate (standard deviation of abrasive flow rate);

[0018] Import the impeller speed into the formula The impeller speed deviation index is obtained from the data. Indicates the impeller speed. Indicates the optimal impeller speed. This indicates the permissible deviation range of impeller speed (standard deviation of impeller speed).

[0019] A velocity-speed adaptation model is constructed based on the scouring condition coefficient, the annular specimen state coefficient, the abrasive velocity deviation index, and the impeller speed deviation index. This velocity-speed adaptation model is expressed as follows:

[0020]

[0021] Where M represents the flow rate-rotation speed fit, Represents the state coefficient of the annular specimen. Indicates the scouring state coefficient. Indicates the abrasive flow rate deviation index. Indicates the impeller speed deviation index. This represents the penalty coefficient for abrasive flow rate deviation. The impeller speed deviation penalty coefficient is represented by the following. , The This indicates the overall fit of the entire test system, and the larger the value, the higher the fit.

[0022] Import the current annular specimen state coefficient, current scouring state coefficient, current abrasive flow velocity deviation index, and impeller speed deviation index into the flow velocity-speed adaptation model to obtain the current flow velocity-speed adaptation degree.

[0023] Further technical solution: The working steps of the scour condition analysis module are as follows:

[0024] The concentricity error between the annular specimen and the impeller is obtained by performing maximum-minimum normalization.

[0025] The wear temperature factor obtained after maximum-minimum normalization of the wear temperature is imported into the formula. The output wear agent temperature index, among which, Indicates the wear coefficient at temperature. Indicates the wear agent temperature factor. Indicates the optimal wear-conductor temperature factor;

[0026] A scouring condition model is constructed based on the wear agent state coefficient, wear agent temperature index, and concentricity error index. The scouring condition model is expressed as follows:

[0027]

[0028] in, Indicates the scouring state coefficient. Indicates the wear condition factor, Indicates the wear agent temperature index. Represents the concentricity sensitivity coefficient. The concentricity error index is represented by the following. The higher the value, the better the scouring effect;

[0029] Import the current abrasive state coefficient, current abrasive temperature index, and current concentricity error index into the scouring state model to obtain the current scouring condition coefficient.

[0030] Further technical solution: The working steps of the wear agent condition analysis module are as follows:

[0031] The sand particle size distribution (the proportion of particles with a diameter of 0.5-1mm) is subjected to maximum-minimum normalization to obtain the sand particle size distribution index.

[0032] The sand hardness factor obtained after performing maximum-min normalization on the sand grain hardness is imported into the formula. The output is the hardness index of the sand particles, among which, Indicates the hardness attenuation coefficient of sand particles. Indicates the hardness factor of sand particles;

[0033] The sand content factor obtained after performing maximum-min normalization on the sand content is imported into the formula. The output sand content index, among which, Indicates the attenuation coefficient of sand content. Indicates the sand content factor. Indicates the optimal sand content factor;

[0034] An abrasive state model is constructed based on the sand particle size distribution index, sand content index, and sand hardness index. The abrasive state model is expressed as follows:

[0035]

[0036] in, Indicates the wear condition factor, Indicates the particle size distribution index of sand. Indicates the hardness index of sand particles. The index represents the sand content. Furthermore, the higher the value, the better the condition of the abrasive.

[0037] Import the current sand particle size distribution index, current sand content index, and current sand hardness index into the abrasive state model to obtain the current abrasive state coefficient.

[0038] Further technical solution: The working steps of the ring specimen state analysis module are as follows:

[0039] After performing maximum-min normalization on the roundness error to obtain the roundness error factor, it is imported into the formula. The output roundness error index is given by, where, This represents the roundness error attenuation coefficient. Indicates the roundness error factor;

[0040] After performing maximum-minimum normalization on the inner ring flatness error and the wall thickness uniformity error, the inner ring flatness error index and the wall thickness uniformity error index are obtained.

[0041] A state model of the annular specimen is constructed based on the roundness error index, the inner ring flatness error index, and the wall thickness uniformity error index. The state model of the annular specimen is expressed as follows:

[0042]

[0043] in, Represents the state coefficient of the annular specimen. Indicates the roundness error index. This indicates the inner ring smoothness error index. Indicates the wall thickness uniformity error index. Represents the weight coefficient and The Furthermore, the larger the value, the better the condition of the annular specimen;

[0044] Import the current roundness error index, the current inner ring flatness error index, and the current wall thickness uniformity error index into the annular specimen state model to output the current annular specimen state coefficient.

[0045] Further technical solutions include: a frame, a bearing cylinder, and a bearing bracket. The bearing cylinder is slidably connected to a slide rail fixedly connected to the frame. The bearing bracket is slidably connected to a guide rod fixedly connected to the frame. An upper plate is fixedly connected to the upper end of the guide rod. The bearing bracket is fixedly connected to the output shaft of a linear motion component B detachably mounted on the upper plate. A circular cavity for placing the annular specimen is provided inside the bearing cylinder. The system also includes:

[0046] The flushing mechanism, mounted on the support frame, is used to drive the abrasive located in the support cylinder to flow and flush the annular specimen.

[0047] The positioning mechanism, mounted on the frame, is used to position the carrier cylinder.

[0048] Further technical solution: The flushing mechanism includes a motor, a linear motion component A, and an impeller. The motor is detachably mounted on the support frame, and the linear motion component A is detachably mounted on the output shaft of the motor. The output shaft of the linear motion component A is fixedly connected to the end of the support frame.

[0049] Further technical solution: The positioning mechanism includes positioning block A and positioning block B. Positioning block A is fixedly connected to the frame, and positioning block B is fixedly connected to the pin. Positioning block A and positioning block B can be connected by the pin.

[0050] A test device for erosion resistance of semi-rigid road base material, using the aforementioned test device for erosion resistance of semi-rigid road base material.

[0051] This invention provides an experimental device for testing the erosion resistance of semi-rigid road base materials, which has the following advantages compared with the prior art:

[0052] 1. This invention can suppress system vibration and parameter fluctuations by using the concentricity error index and flow velocity deviation penalty coefficient, thus ensuring the stability of the scouring process. At the same time, it can quantify the influence of non-geometric factors such as sand hardness, particle size distribution, and temperature based on the normalization and exponential decay model, thus solving the defect of traditional methods that ignore the characteristics of abrasives. Finally, it uses a multi-level state analysis model (ring specimen state coefficient, abrasive state coefficient, and scouring condition coefficient) to calculate the flow velocity-rotation speed fit in real time, driving the impeller to dynamically adjust the height above the bottom, which significantly improves the physical simulation accuracy of the scouring experiment. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the process of the present invention.

[0054] Figure 2 This is a three-dimensional structural diagram of the present invention.

[0055] Figure 3 This is a schematic diagram of the overall structure of the present invention.

[0056] Figure reference numerals: 1. Frame; 2. Slide rail; 3. Bearing cylinder; 4. Upper plate; 5. Guide rod; 6. Bearing frame; 7. Flushing mechanism; 701. Motor; 702. Linear motion component A; 703. Impeller; 8. Positioning mechanism; 801. Positioning block A; 802. Positioning block B; 803. Pin; 9. Linear motion component B; 10. Annular specimen. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0058] In existing technologies, the erosion resistance testing of semi-rigid road base materials mainly relies on experimental setups with fixed impeller heights and static erosion conditions. These setups cannot dynamically adjust to changes in specimen geometry, abrasive properties, and erosion conditions, leading to significant deviations between experimental results and actual working conditions. For example, when the specimen has an uneven inner ring or uneven wall thickness, a fixed impeller height exacerbates the uneven distribution of erosion force; when the abrasive particle size distribution deviates from the ideal range or temperature fluctuates, traditional setups lack parameter compensation mechanisms, affecting test accuracy.

[0059] To address the aforementioned issues, the inventors discovered that experimental errors primarily stem from the cumulative effects of geometric defects in the specimen, fluctuations in the abrasive's condition, and mismatches in scouring conditions. Through analysis of the scouring mechanism, it was recognized that the impeller's height above the bottom needs to dynamically adapt to the specimen's condition and the abrasive's properties, rather than remaining fixed. Based on this, a parameterized modeling of the specimen's geometric parameters, abrasive properties, and scouring conditions was proposed, establishing a multi-dimensional collaborative analysis system. This system optimizes the impeller position through real-time calculation of the fit, enabling dynamic matching of the scouring depth with the experimental conditions.

[0060] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0061] Please see Figure 1 An erosion resistance testing device for semi-rigid road base materials, provided in one embodiment of the present invention, includes:

[0062] The impeller clearance height adjustment system is used to dynamically adjust the impeller clearance height, including:

[0063] The ring specimen state analysis module constructs a ring specimen state model based on the inner ring flatness error, wall thickness uniformity error, and roundness error, and outputs the ring specimen state coefficients.

[0064] The wear agent condition analysis module constructs an wear agent condition model based on sand hardness, sand content, and sand particle size distribution (0.5-1mm particle size percentage) and outputs wear agent condition coefficients.

[0065] The scouring condition analysis module constructs a scouring condition model based on the abrasive temperature under the abrasive state coefficient and the concentricity of the annular specimen and the impeller, and outputs the scouring condition coefficient.

[0066] The scouring state analysis module constructs a velocity-speed adaptation model based on the abrasive flow rate and impeller speed under the scouring condition coefficient and the state coefficient of the annular specimen, and outputs the velocity-speed adaptation degree.

[0067] The impeller clearance height optimization module constructs an impeller clearance height optimization model based on the baseline clearance height and the flow velocity-rotation speed adaptation, and outputs the target impeller clearance height.

[0068] The impeller clearance height adjustment system refers to a dynamic adjustment device for the impeller position achieved through multi-module collaborative analysis. It can utilize linear motion components (such as electric actuators) in conjunction with displacement sensors to achieve closed-loop control. The annular specimen state analysis module is a processing unit that quantifies the impact of specimen geometric errors on scouring uniformity. Specifically, it uses a laser scanner to collect three-dimensional morphological data of the specimen and calculates state coefficients using a normalization algorithm. The abrasive state analysis module is a processing unit that evaluates the impact of sand particle properties on scouring capacity. Specifically, it uses a particle size analyzer and hardness tester to obtain sand particle parameters and calculates state coefficients using an exponential decay model. The scouring condition analysis module is a processing unit that analyzes the impact of temperature and concentricity on the scouring trajectory. Specifically, it uses an infrared temperature sensor and optical alignment instrument to collect data and calculates scouring condition coefficients through normalization processing and an exponential model. The scouring state analysis module is an energy transfer optimization unit that matches flow velocity and rotational speed. Specifically, it uses a flow meter and encoder to monitor parameters in real time and calculates the fit degree using the square of the deviation. The impeller clearance height optimization module is a decision-making unit that dynamically adjusts the height based on the fit. Specifically, an exponential function model can be used to map the fit into the height adjustment amount.

[0069] Specifically, the annular specimen state analysis module acquires data on the flatness, wall thickness uniformity, and roundness of the inner ring of the specimen through laser scanning. After normalization, this data is input into the state model, and the output is a state coefficient reflecting the geometric integrity of the specimen. When the specimen has roundness deviations, this coefficient decreases, triggering the height adjustment system to compensate for the scouring force distribution. The abrasive state analysis module monitors the hardness, content, and particle size distribution of the abrasive particles in real time. When the proportion of 0.5-1mm abrasive particles is insufficient, the state coefficient decreases, indicating that the impeller height needs to be adjusted to maintain the scouring intensity. The scouring condition analysis module combines abrasive temperature and specimen-impeller concentricity data. When the temperature deviates from the optimal range or the concentricity error increases, the scouring condition coefficient decreases, and the system automatically corrects the impeller position to offset fluid viscosity changes and eccentric scouring effects. The scouring state analysis module simultaneously collects abrasive flow velocity and impeller speed, and outputs a fit degree reflecting energy transfer efficiency by calculating the flow velocity deviation index and speed deviation index. The impeller clearance optimization module dynamically adjusts the impeller position based on the exponential relationship between the fit and the reference height, so that the scouring depth matches the specimen condition, abrasive characteristics and scouring conditions in real time.

[0070] Compared to existing technologies, traditional devices employ a fixed impeller height and ignore the dynamic influence of specimen geometric errors and abrasive conditions, resulting in simplistic scouring conditions. This proposed solution utilizes multi-module collaborative analysis to transform specimen geometric parameters, sand particle properties, and scouring conditions into quantifiable coefficients, establishing a height optimization model for dynamic adjustment. For example, when the specimen exhibits uneven wall thickness, traditional devices, due to their fixed height, lead to excessive scouring in thin-walled areas. This solution, however, automatically increases the impeller height by reducing the fit, minimizing differences in scouring pressure gradients. When sand particle size distribution deviates from the ideal range, traditional devices cannot compensate for scouring intensity loss, while this solution adjusts the impeller position using the abrasive condition coefficient to maintain effective scouring energy.

[0071] Through the above technical solution, this application can dynamically optimize the impeller height from the bottom based on the real-time changes in the specimen geometry, abrasive properties, and scouring conditions, solving the problem of uneven scouring force distribution caused by parameter mismatch in traditional devices. This solution eliminates the influence of specimen processing errors on experimental results through a quantitative model, compensates for abrasive property fluctuations through sand particle state analysis, and maintains scouring energy transfer efficiency through flow velocity-rotation speed adaptation, thereby improving the repeatability of experimental data and the accuracy of operating condition simulation.

[0072] Preferably, the working steps of the annular specimen state analysis module are as follows:

[0073] After performing maximum-min normalization on the roundness error to obtain the roundness error factor, it is imported into the formula. The output roundness error index is given by, where, This represents the roundness error attenuation coefficient. Indicates the roundness error factor;

[0074] After performing maximum-minimum normalization on the inner ring flatness error and the wall thickness uniformity error, the inner ring flatness error index and the wall thickness uniformity error index are obtained.

[0075] A state model of the annular specimen is constructed based on the roundness error index, the inner ring flatness error index, and the wall thickness uniformity error index. The state model of the annular specimen is expressed as follows:

[0076]

[0077] in, Represents the state coefficient of the annular specimen. Indicates the roundness error index. This indicates the inner ring smoothness error index. Indicates the wall thickness uniformity error index. Represents the weight coefficient and The Furthermore, the larger the value, the better the condition of the annular specimen;

[0078] Import the current roundness error index, the current inner ring flatness error index, and the current wall thickness uniformity error index into the annular specimen state model to output the current annular specimen state coefficient.

[0079] Among them, roundness error refers to the degree of deviation of the cross-section of the annular specimen from the ideal circle. Specifically, it can be achieved by measuring the radial distance of multiple points on the circumference of the specimen using a laser scanner and calculating the standard deviation. This error affects the uniformity of stress on the specimen during scouring. Roundness error factor is a standardized parameter that maps the original error value to the 0-1 interval. Specifically, it can be achieved by processing the original measurement data using a maximum-minimum normalization formula, used to eliminate the influence of different dimensions on model calculations. Roundness error index is a parameter obtained by nonlinearly transforming the error factor using an exponential function. Specifically, it can be achieved by converting the normalized error factor using an exponential decay model, reflecting the sensitivity of the error to the specimen's state. Inner ring flatness error refers to the degree of deviation of the inner ring surface of the specimen from the ideal plane. Specifically, it can be achieved by scanning the inner ring surface with a 3D profilometer and calculating the standard deviation of the height difference. This error affects the stability of the scouring flow field. Wall thickness uniformity error refers to the degree of fluctuation in the wall thickness dimension of the specimen along the circumference. Specifically, it can be achieved by measuring multiple points at equal intervals along the circumference with an ultrasonic thickness gauge and calculating the thickness range. This error leads to uneven distribution of structural strength in the specimen.

[0080] Specifically, the ring specimen state analysis module first normalizes the roundness error, converting it into a dimensionless error factor. Then, it generates a roundness error exponent using an exponential function. This exponent decays exponentially with increasing error, reinforcing the nonlinear impact of error on the state coefficient. The inner ring flatness error and wall thickness uniformity error are each normalized and converted into standardized exponents to avoid distortion of evaluation results due to dimensional differences in a single error. The three error indices are then fused into a comprehensive state coefficient using a weighted summation model. The weighting coefficients are allocated according to the degree of influence of each error type on the scour experiment; for example, the roundness error weight can be set to 0.5, while the inner ring flatness and wall thickness uniformity errors each account for 0.25. This model transforms discrete geometric errors into continuous state coefficients, providing quantitative input parameters for subsequent scour condition optimization.

[0081] Compared with existing technologies, traditional experimental setups rely solely on visual inspection or single-dimensional measurements to determine the specimen's condition, failing to quantitatively assess the combined effects of roundness, inner ring flatness, and wall thickness uniformity. This approach eliminates dimensional differences through multi-dimensional error normalization, enhances the sensitivity to key errors by combining an exponential decay model, and finally establishes a condition assessment model through weighted fusion, thus resolving the problem of distorted scour experimental data caused by specimen geometric errors.

[0082] Through the above technical solution, this application can accurately quantify the comprehensive geometric state of the annular specimen, transforming the influence of roundness error, inner ring flatness error, and wall thickness uniformity error on the scouring experiment into calculable coefficients, thus avoiding inaccurate experimental condition settings due to specimen preparation errors. These state coefficients, as input parameters for the subsequent impeller height optimization model, can dynamically adjust the scouring conditions to match the actual state of the specimen, thereby improving the consistency between experimental data and actual working conditions.

[0083] Preferably, the working steps of the wear agent condition analysis module are as follows:

[0084] The sand particle size distribution (the proportion of particles with a diameter of 0.5-1mm) is subjected to maximum-minimum normalization to obtain the sand particle size distribution index.

[0085] The sand hardness factor obtained after performing maximum-min normalization on the sand grain hardness is imported into the formula. The output is the hardness index of the sand particles, among which, Indicates the hardness attenuation coefficient of sand particles. Indicates the hardness factor of sand particles;

[0086] The sand content factor obtained after performing maximum-min normalization on the sand content is imported into the formula. The output sand content index, among which, Indicates the attenuation coefficient of sand content. Indicates the sand content factor. Indicates the optimal sand content factor;

[0087] An abrasive state model is constructed based on the sand particle size distribution index, sand content index, and sand hardness index. The abrasive state model is expressed as follows:

[0088]

[0089] in, Indicates the wear condition factor, Indicates the particle size distribution index of sand. Indicates the hardness index of sand particles. The index represents the sand content. Furthermore, the higher the value, the better the condition of the abrasive.

[0090] Import the current sand particle size distribution index, current sand content index, and current sand hardness index into the abrasive state model to obtain the current abrasive state coefficient.

[0091] Among them, the sand particle size distribution index refers to the standardized value of the proportion of 0.5-1mm particles after normalization. Specifically, the maximum-minimum normalization method can be used to map the original proportion to the 0-1 range to characterize the rationality of the particle size distribution. The sand hardness index is a quantitative index of the normalized hardness factor after exponential decay. Specifically, it can be used as follows: Function calculation, using the hardness attenuation coefficient Adjusting the degree to which hardness inhibits the state. The sand content index is a deviation penalty index of the normalized content factor from the optimum value, which can be specifically used as... Function calculation, using the content decay coefficient Controlling deviation sensitivity. The wear agent state model is a mathematical model that fuses three indices through a product relationship; specifically, it can employ... The formula allows the advantages of gradation to offset the negative impact of hardness, while retaining the ability to adjust the content.

[0092] Specifically, the sand particle size distribution is first converted into a standard index. For example, when the proportion of 0.5-1mm particles is 65%, a gradation index of 0.8 can be obtained after normalization. The sand hardness is obtained through Mohs hardness testing to obtain raw data, which is then normalized and input into the exponential function. For example, when... When the value is 0.5, a hardness factor of 0.6 will generate a hardness index of 0.74. The normalized sand content is compared with a preset optimal value; for example, when the actual content deviates from the optimal value by 20%, Setting the value to 1.2 will cause the content index to decrease to 0.45. Multiplying the three indices yields a comprehensive state coefficient; for example, when the gradation index is 0.8, the hardness index is 0.3, and the content index is 0.9, the final state coefficient is 0.216. This model achieves dynamic evaluation of the wear agent's state through the coupling relationship of the positive effect of gradation, the negative inhibition of hardness, and the adjustment of content balance.

[0093] Compared to existing technologies, traditional methods only use a single sand particle parameter for evaluation, such as considering only sand particle hardness or a fixed gradation range. This scheme, for the first time, establishes a mathematical model using particle size distribution as an independent variable, and simultaneously introduces a hardness decay function and a content deviation penalty mechanism, forming a multi-parameter synergistic evaluation system. Existing technologies lack quantitative control over the dynamic deviation of sand particle content, while this scheme enhances the sensitivity of content control through an exponential penalty function.

[0094] Through the above technical solution, this application can automatically generate the abrasive state coefficient based on the dynamic changes in sand particle hardness, content, and gradation, eliminating the limitations of single-parameter evaluation. When the sand particle gradation is optimized, it can partially offset the negative impact of high hardness; when the sand particle content deviates from the optimal value, the model automatically reduces the state coefficient to reflect the deterioration of experimental conditions. This solution solves the problem that traditional devices cannot dynamically adapt to changes in sand particle characteristics, enabling precise matching between scouring experimental conditions and the actual state of the abrasive, thereby improving the repeatability and accuracy of experimental results.

[0095] Preferably, the working steps of the scour condition analysis module are as follows:

[0096] The concentricity error between the annular specimen and the impeller is obtained by performing maximum-minimum normalization.

[0097] The wear temperature factor obtained after maximum-minimum normalization of the wear temperature is imported into the formula. The output wear agent temperature index, among which, Indicates the wear coefficient at temperature. Indicates the wear agent temperature factor. Indicates the optimal wear-conductor temperature factor;

[0098] A scouring condition model is constructed based on the wear agent state coefficient, wear agent temperature index, and concentricity error index. The scouring condition model is expressed as follows:

[0099]

[0100] in, Indicates the scouring state coefficient. Indicates the wear condition factor, Indicates the wear agent temperature index. Represents the concentricity sensitivity coefficient. The concentricity error index is represented by the following. The higher the value, the better the scouring effect;

[0101] Import the current abrasive state coefficient, current abrasive temperature index, and current concentricity error index into the scouring state model to obtain the current scouring condition coefficient.

[0102] The concentricity error index refers to the conversion of the concentricity error into a standardized parameter within the range of 0-1 using a maximum-minimum normalization method. Specifically, a linear transformation formula can be used to map the measured concentricity error value to a preset error range, and then normalization is applied to eliminate dimensional differences. This index is used to quantify the degree of influence of the installation deviation between the specimen and the impeller on the uniformity of fluid distribution.

[0103] The wear agent temperature factor refers to a standardized temperature parameter obtained by normalizing the measured temperature value. Specifically, the temperature value can be linearly scaled according to a preset temperature range so that the temperature parameter is within the 0-1 range. This factor is used to eliminate differences in temperature dimensions and establish comparability with the optimal temperature.

[0104] Among them, the exponential decay function refers to the function that uses the natural constant. The exponential function with base 1 can be specifically expressed as: ,in This is the temperature decay coefficient. This function exponentially strengthens the penalty effect when the temperature deviates from the optimal value, making the influence of the temperature parameter on the scouring state exhibit a non-linear decay characteristic.

[0105] The scouring condition model refers to the product relationship composed of the wear agent state coefficient, temperature index, and concentricity error index, specifically in the form of: The model achieves multi-parameter coupling through product operations, where the exponential term is used to correct the negative impact of concentricity error on scouring uniformity.

[0106] Specifically, the scour condition analysis module first converts the concentricity error into a standardized exponent, eliminating the dimensional differences in mechanical installation errors. Simultaneously, the temperature parameter is normalized and imported into an exponential function, transforming the degree of temperature deviation from the optimal value into an exponential decay factor. Subsequently, the abrasive state coefficient is multiplied by the temperature exponent to characterize the combined effect of sand particle physical properties and fluid viscosity, and then the concentricity error is nonlinearly corrected using an exponential term. This model achieves multi-parameter synergy through a multiplicative relationship, where the exponential decay term effectively suppresses localized scour intensity anomalies caused by concentricity errors, while the temperature exponent enhances the sensitive response of fluid viscosity changes to the scour state. The resulting scour state coefficient dynamically reflects the combined influence of abrasive temperature, specimen installation accuracy, and sand particle condition.

[0107] Compared to existing technologies, traditional methods only use fixed thresholds to determine scouring conditions, failing to consider the dynamic impact of temperature changes on fluid properties and lacking a quantitative relationship between concentricity error and scouring uniformity. This proposed solution eliminates parameter dimensional differences through normalization and establishes a nonlinear relationship between temperature sensitivity and concentricity error using an exponential function, enabling dynamic evaluation of scouring conditions under multi-parameter coupling. Compared to static threshold judgment, this model can automatically adjust scouring condition coefficients based on real-time parameters, resolving the problem of unstable scouring intensity caused by temperature fluctuations and mechanical positioning deviations.

[0108] Through the above technical solution, this application can quantify the impact of temperature deviation from the optimal value on fluid viscosity in real time, accurately assess the scouring non-uniformity caused by concentricity error, and dynamically adjust the scouring state coefficient through a nonlinear model. This effectively suppresses changes in abrasive flow characteristics caused by temperature fluctuations, reduces localized scouring anomalies caused by specimen installation deviations, and significantly improves the uniformity and stability of fluid distribution during scouring experiments.

[0109] Preferably, the working principle of the scour status analysis module is as follows:

[0110] Import the abrasive flow rate into the formula The wear agent flow rate deviation index is obtained from the data. Indicates the abrasive flow rate. Indicates the optimal flow rate of the abrasive. Indicates the permissible deviation range of abrasive flow rate (standard deviation of abrasive flow rate);

[0111] Import the impeller speed into the formula The impeller speed deviation index is obtained from the data. Indicates the impeller speed. Indicates the optimal impeller speed. This indicates the permissible deviation range of impeller speed (standard deviation of impeller speed).

[0112] A velocity-speed adaptation model is constructed based on the scouring condition coefficient, the annular specimen state coefficient, the abrasive velocity deviation index, and the impeller speed deviation index. This velocity-speed adaptation model is expressed as follows:

[0113]

[0114] Where M represents the flow rate-rotation speed fit, Represents the state coefficient of the annular specimen. Indicates the scouring state coefficient. Indicates the abrasive flow rate deviation index. Indicates the impeller speed deviation index. This represents the penalty coefficient for abrasive flow rate deviation. The impeller speed deviation penalty coefficient is represented by the following. , The This indicates the overall fit of the entire test system, and the larger the value, the higher the fit.

[0115] Import the current annular specimen state coefficient, current scouring state coefficient, current abrasive flow velocity deviation index, and impeller speed deviation index into the flow velocity-speed adaptation model to obtain the current flow velocity-speed adaptation degree.

[0116] The abrasive flow velocity deviation index is a quantitative indicator calculated by taking the square of the difference between the actual flow velocity and the optimal flow velocity relative to the allowable deviation range. Specifically, it can be achieved by collecting data from a flow velocity sensor and normalizing it using the standard deviation. This index characterizes the degree to which the flow velocity deviates from the ideal state. The impeller speed deviation index is also a quantitative indicator calculated by taking the square of the difference between the actual speed and the optimal speed relative to the allowable deviation range. This can be achieved by measuring speed data using an encoder and then processing it using the standard deviation. This index reflects the impact of speed fluctuations on scouring uniformity. The flow velocity-speed adaptation model is a mathematical model that exponentially weights and integrates the specimen state, scouring conditions, and flow velocity-speed deviations. Specifically, it can be implemented using an exponential function combined with the product of the annular specimen state coefficient and the scouring condition coefficient. This model is used to dynamically evaluate the overall system adaptation level.

[0117] Specifically, the scouring state analysis module eliminates the incomparability between parameters of different dimensions by calculating the standardized deviation exponents of flow velocity and rotational speed, and amplifies the impact of abnormal deviations on the system through squaring operations. The annular specimen state coefficient reflects the constraint of specimen geometric defects on scouring uniformity, while the scouring condition coefficient characterizes the interference of abrasive temperature and concentricity errors on scouring stability. The exponential penalty term dynamically suppresses flow velocity and rotational speed deviations through positive coefficients, enabling the fit to comprehensively characterize the degree of matching between specimen state, scouring conditions, and flow velocity and rotational speed. When the specimen state deteriorates or scouring conditions worsen, the model automatically reduces the fit output, triggering the impeller height adjustment mechanism.

[0118] Compared with existing technologies, traditional experimental setups use fixed flow rate and rotation speed parameters, which cannot be dynamically adjusted according to the geometric errors of the specimen and the characteristics of the abrasive, resulting in a mismatch between the scouring conditions and the specimen state. This scheme, by establishing a multi-dimensional parameter fusion adaptation model, achieves dynamic matching of specimen state, abrasive characteristics, and scouring conditions for the first time, overcoming the problem of experimental error accumulation caused by parameter fixation in traditional methods.

[0119] Through the above technical solution, this application can sense the influence of flow velocity and rotational speed deviation on the scouring process in real time, and dynamically adjust the fit evaluation criteria in combination with changes in specimen condition and scouring conditions, providing accurate quantitative basis for optimizing the impeller height from the bottom. This solution effectively solves the problem of mismatch between scouring conditions and specimen condition caused by fixed parameters in traditional experimental devices, and significantly improves the repeatability of scouring resistance experiments and the realism of operating condition simulation.

[0120] Preferably, the highly optimized model is represented as:

[0121]

[0122] in, Indicates the height of the target impeller from the bottom. Indicates the height of the reference impeller from the bottom. This represents the fitness sensitivity coefficient. This indicates the flow rate-rotation speed fit threshold. This indicates the flow rate-rotation speed compatibility.

[0123] The reference impeller height refers to the initially set distance between the impeller and the bottom of the specimen, which can be determined through calibration experiments or historical data, providing a basic reference for dynamic adjustment. The fit sensitivity coefficient refers to the weight of the influence of flow velocity-rotation speed fit changes on the height adjustment range, which can be determined through calibration experiments or optimization algorithms, used to control the adjustment intensity under different fit deviations. The flow velocity-rotation speed fit threshold refers to the minimum allowable fit critical value of the system, which can be determined through expert experience calibration, experimental statistics, or theoretical calculations, used to determine whether the scouring conditions deviate from the normal range. The flow velocity-rotation speed fit model is a mathematical model that exponentially weights and fuses the specimen state, scouring conditions, and flow velocity-rotation speed deviations. Specifically, it can be implemented using an exponential function combined with the product of the annular specimen state coefficient and the scouring condition coefficient, used to dynamically evaluate the overall fit level of the system and quantify the coordination of the current scouring state.

[0124] Specifically, when the actual flow rate-rotation speed fit is below the threshold, the exponential term... The value increases, leading to an increase in the target height. Relative to reference height The target height is reduced to lower the impeller position and enhance scouring intensity; when the fit exceeds a threshold, the target height is increased to weaken the scouring effect. Fit sensitivity coefficient. By adjusting the curvature of the exponential function, the sensitivity of height adjustment to fit deviations can be controlled. For example, when When the value is large, the same fit deviation will lead to a more significant height change, which is suitable for scenarios that are sensitive to fluctuations in scour conditions; when When the value is small, the height adjustment tends to be gradual, which is suitable for scenarios that require stable scouring intensity.

[0125] Compared with existing technologies, traditional experimental setups use a fixed impeller height, which cannot be adaptively adjusted according to dynamic changes in specimen condition, abrasive properties, and scouring conditions, resulting in systematic deviations between experimental data and actual operating conditions. This solution, however, establishes a height optimization model, embedding the mathematical relationship between flow velocity-rotation speed adaptation and impeller position into the control logic. This enables real-time feedback adjustment of scouring intensity, solving the problem of rigid experimental conditions caused by a fixed height.

[0126] Through the above technical solution, this application can automatically optimize the impeller height from the bottom according to the dynamic changes in scouring conditions, so that the scouring intensity matches the specimen condition and abrasive characteristics, thereby improving the accuracy and repeatability of experimental data. For example, when the specimen surface experiences localized wear due to scouring, the decreased fit triggers a reduction in impeller height to compensate for the loss of scouring intensity; when the abrasive temperature increases, leading to enhanced fluidity, the increased fit triggers an increase in impeller height to avoid excessive scouring. This closed-loop adjustment mechanism makes the experimental conditions closer to actual road scouring conditions.

[0127] Please see Figure 2 as well as Figure 3 An erosion resistance testing device for semi-rigid road base materials includes a frame 1, a bearing cylinder 3, and a bearing frame 6. The bearing cylinder 3 is slidably connected to a slide rail 2 fixedly connected to the frame 1. The bearing frame 6 is slidably connected to a guide rod 5 fixedly connected to the frame 1. An upper plate 4 is fixedly connected to the upper end of the guide rod 5. The bearing frame 6 is fixedly connected to the output shaft of a linear motion component B9 detachably mounted on the upper plate 4. The bearing cylinder 3 has a circular cavity (not shown in the figure) for placing an annular specimen 10. The device also includes:

[0128] The flushing mechanism 7, mounted on the support frame 6, is used to drive the abrasive in the support cylinder 3 to flow and flush the annular specimen 10.

[0129] Positioning mechanism 8, installed on frame 1, is used to position the bearing cylinder 3;

[0130] The flushing mechanism 7 includes a motor 701, a linear motion component A702, and an impeller 703. The motor 701 is detachably mounted on the support frame 6. The linear motion component A702 is detachably mounted on the output shaft of the motor 701. The output shaft of the linear motion component A702 passes through the end of the support frame 6 and is fixedly connected to the impeller 703. The purpose of this arrangement is to use the motor 701 to drive the linear motion component A702 to drive the impeller 703 to rotate, and then use the impeller 703 to drive the abrasive in the circular cavity to flow, so as to achieve the technical effect of flushing the annular specimen 10. At the same time, the linear motion component A702 can drive the impeller 703 to perform linear motion in the vertical direction, so as to adjust the height of the impeller 703 from the bottom (the distance between the bottom of the impeller 703 and the bottom wall of the circular cavity).

[0131] The positioning mechanism 8 includes positioning block A801 ​​and positioning block B802. Positioning block A801 ​​is fixedly connected to the frame 1, and positioning block B802 is fixedly connected to the pin 803. Positioning block A801 ​​and positioning block B802 can be connected by pin 803. The purpose of this arrangement is to use positioning block A801 ​​and positioning block B802 in conjunction with pin 803 to position and limit the position of the bearing cylinder 3.

[0132] In this embodiment of the invention, after the annular specimen 10 is placed in the bearing cylinder 3, the positioning mechanism 8 is used to limit the bearing cylinder 3. At the same time, the linear motion component B9 is used to push the bearing frame 6 to move linearly and cause the bottom of the bearing frame 6 to cover the bearing cylinder 3. At this time, the flushing mechanism 7 is activated to drive the abrasive in the bearing cylinder 3 to flow and flush the annular specimen 10.

[0133] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0134] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A device for testing the resistance of a road semi-rigid base material to erosion, characterized in that it comprises: Comprise: Impeller off-bottom height adjustment system for dynamic adjustment of impeller off-bottom height, comprising: Annular test piece state analysis module, based on annular test piece inner ring flatness error, wall thickness uniformity error and roundness error, constructs annular test piece state model to output annular test piece state coefficient; Wear agent state analysis module, based on sand particle hardness, sand particle content and sand particle size gradation, constructs wear agent state model to output wear agent state coefficient; Erosion condition analysis module, based on wear agent temperature under wear agent state coefficient and annular test piece and impeller concentricity, constructs erosion state model to output erosion condition coefficient; Erosion state analysis module, based on erosion condition coefficient and wear agent flow rate under annular test piece state coefficient and impeller rotating speed, constructs flow rate-rotating speed adaptation model to output flow rate-rotating speed adaptation degree; Impeller off-bottom height optimization module, based on reference off-bottom height and flow rate-rotating speed adaptation degree, constructs impeller off-bottom height optimization model to output target impeller off-bottom height.

2. The device for testing the resistance to washout of a road semi-rigid base material according to claim 1, characterized in that, The height optimization model is expressed as: wherein, represents a target impeller height from the bottom, represents a reference impeller height from the bottom, represents an adaptation sensitivity coefficient, represents a flow rate - speed adaptation threshold, represents a flow rate - speed adaptation.

3. The device for testing the resistance to washout of a road semi-rigid base material according to claim 2, characterized in that, The working principle of the erosion state analysis module is: The wear agent flow rate is introduced into the formula to obtain a wear agent flow rate bias index, wherein, represents the wear agent flow rate, represents the optimal wear agent flow rate, represents the allowable bias range of the wear agent flow rate (wear agent flow rate standard deviation); The impeller rotation speed is introduced into the formula to obtain an impeller rotation speed deviation index, wherein, represents the impeller rotation speed, represents the optimal impeller rotation speed, represents the allowable deviation range of the impeller rotation speed (impeller rotation speed standard deviation); Based on the erosion condition coefficient, the annular test piece state coefficient, the wear agent flow rate deviation index and the impeller rotating speed deviation index, the flow rate-rotating speed adaptation model is constructed, and the flow rate-rotating speed adaptation model is expressed as: wherein M represents a flow rate - rotational speed fitness, represents a ring specimen state coefficient, represents an erosion state coefficient, represents an abrasives flow rate deviation index, represents an impeller rotational speed deviation index, represents an abrasives flow rate deviation penalty coefficient, represents an impeller rotational speed deviation penalty coefficient, said , , said represents a comprehensive fitness of the entire test system and the greater the value the higher the fitness. The current annular test piece state coefficient, the current erosion state coefficient, the current wear agent flow rate deviation index and the impeller rotating speed deviation index are introduced into the flow rate-rotating speed adaptation model to obtain the current flow rate-rotating speed adaptation degree.

4. The device for testing the resistance to washout of a road semi-rigid base material according to claim 3, characterized in that, The working steps of the erosion condition analysis module are: The annular test piece and the impeller concentricity error are maximum-minimum normalized to obtain the concentricity error index; The abrasion agent temperature factor obtained by maximum-minimum normalization of the abrasion agent temperature is introduced into the formula The abrasion agent temperature index is outputted from the middle, wherein, represents the abrasion agent temperature attenuation coefficient, represents the abrasion agent temperature factor, represents the optimal abrasion agent temperature factor; Based on the wear agent state coefficient, the wear agent temperature index and the concentricity error index, the erosion condition model is constructed, and the erosion condition model is expressed as: wherein, represents a washout condition coefficient, represents an abrasives condition coefficient, represents an abrasives temperature index, represents a concentricity sensitivity coefficient, represents a concentricity error index, said and the greater the value the better the washout condition; The current wear agent state coefficient, the current wear agent temperature index and the current concentricity error index are introduced into the erosion state model to obtain the current erosion condition coefficient.

5. The device for testing the resistance to washout of a semi-rigid base material for roads according to claim 3, characterized in that, The working steps of the wear agent state analysis module are: The sand particle size gradation is maximum-minimum normalized to obtain the sand particle size gradation index; The sand hardness factor obtained by maximum-minimum normalizing the sand hardness is introduced into the formula The sand hardness index is output from the center, wherein The sand hardness attenuation coefficient is represented by The sand hardness factor is represented by The sand content factor obtained by maximum-minimum normalization of the sand content is introduced into the formula The sand content index is outputted from the middle, wherein, The sand content attenuation coefficient is represented by, The sand content factor is represented by, The optimal sand content factor is represented by; Based on the sand particle size gradation index, the sand particle content index and the sand particle hardness index, the wear agent state model is constructed, and the wear agent state model is expressed as: wherein, represents the wear agent condition coefficient, represents the sand grain size gradation index, represents the sand grain hardness index, represents the sand grain content index, said and the greater the value the better the wear agent condition; The current sand particle size gradation index, the current sand particle content index and the current sand particle hardness index are introduced into the wear agent state model to obtain the current wear agent state coefficient.

6. The device for testing the resistance to washout of a semi-rigid base material for roads according to claim 3, characterized in that, The working steps of the annular test piece state analysis module are: The roundness error is normalized by maximum-minimum to obtain a roundness error factor, which is introduced into the formula The roundness error index is outputted, wherein, The roundness error attenuation coefficient is represented by, The roundness error factor is represented by, The inner ring flatness error and the wall thickness uniformity error are maximum-minimum normalized to obtain the inner ring flatness error index and the wall thickness uniformity error index; Based on the roundness error index, the inner ring flatness error index and the wall thickness uniformity error index, the annular test piece state model is constructed, and the annular test piece state model is expressed as: wherein, represents a ring specimen condition coefficient, represents a roundness error index, represents an inner ring flatness error index, represents a wall thickness uniformity error index, represents a weight coefficient and , the and the greater the value, the better the ring specimen condition; The current roundness error index, the current inner ring flatness error index and the current wall thickness uniformity error index are introduced into the annular test piece state model to output the current annular test piece state coefficient.

7. The device for testing the resistance to washout of a semi-rigid base material of a road according to any one of claims 1 to 6, characterized in that, It also includes a rack, a bearing cylinder and a bearing frame, the bearing cylinder is in sliding fit with the slide rail fixedly connected to the rack, the bearing frame is in sliding fit with the guide rod fixedly connected to the rack, the upper end of the guide rod is fixedly connected with an upper plate, the bearing frame is fixedly connected with the output shaft of the linear motion part B detachably installed on the upper plate, a circular cavity for placing the annular test piece is arranged in the bearing cylinder, and the rack further includes: A flushing mechanism is installed on the bearing frame and is used for driving the abrasion agent in the bearing cylinder to flow and flush the annular test piece. A positioning mechanism is installed on the rack and is used for positioning the bearing cylinder.

8. The device for testing the resistance to washout of a road semi-rigid base material according to claim 7, characterized in that, The flushing mechanism includes a motor, a linear motion part A and an impeller, the motor is detachably installed on the bearing frame, the output shaft of the motor is detachably installed with the linear motion part A, and the output shaft of the linear motion part A is fixedly connected with the impeller penetrating through the end of the bearing frame.

9. The device for testing the resistance to washout of a semi-rigid base material for roads according to claim 7, characterized in that, The positioning mechanism includes a positioning block A and a positioning block B, the positioning block A is fixedly connected to the rack, the positioning block B is fixedly connected to the pin shaft, and the positioning block A and the positioning block B can be connected through the pin shaft.

Images